- You can get the code here: github.com/StatQuest/decoder_transformer_from_scratch - Learn more about GiveInternet.org: giveinternet.org/StatQuest NOTE: Donations up to $30 will be matched by an Angel Investor - so a $30 donation would give $60 to the organization. DOUBLE BAM!!! - The full Neural Networks playlist, from the basics to AI, is here: kzread.info/dash/bejne/daWDyMttYa_MdNo.html - Support StatQuest by buying my book The StatQuest Illustrated Guide to Machine Learning or a Study Guide or Merch!!! statquest.org/statquest-store/

Can't imagine the work that goes into this, writing the code, making diagrams, recording, editing and voice over, you're the goat big J.

@statquest

Күн бұрын

Thanks!

You said this was going to come out at the end of May. And I’ve been waiting for this for 2 months. Finally, it’s out 😂

@statquest

Күн бұрын

I guess better later than never?

It is party time! Thanks for uploading!

@statquest

Күн бұрын

You bet!

Cool, learn a lot from all of your videos Josh! 🤯

@statquest

Күн бұрын

Thanks!

sir you deserved millions of views on your KZread ❤❤🎉

@statquest

Күн бұрын

Thanks!

You will be rememberd for next 1000 years in the history of Statistics and Data Science , You should be named as "Father of Applied Statics & Machine Learning " , Pls thumbs up if you are with me

@statquest

Күн бұрын

BAM! :)

HUGE RESPECT for all the work you put into your videos

Finally greatly watied video arrived. Thank you.

@statquest

Күн бұрын

Bam! :)

as always, wonderful content. Thanks :)

@statquest

Күн бұрын

Thanks again!

Today we learned that statquest is awesome. triple BAM!

@statquest

Күн бұрын

Thanks!

Thank you I was in need of this 😊

@statquest

Күн бұрын

Glad it was helpful!

I'm gonna enjoy this one!

@statquest

Күн бұрын

bam! :)

Great and very didactic as usual, Josh!! Definitely going to wrap my head around this for a while and try a few tweaks! Do you plan on eventually also discussing other non-NLP topics like GANs and Diffusion Models?

@statquest

Күн бұрын

One day I hope to.

Thank you! You're the best!!!

@statquest

Күн бұрын

You're welcome!

This will be awesome. I am trying to learn the math behind transformers and PyTorch so hopefully this helps give me some intuition

@statquest

Күн бұрын

I've got a video all about the math behind transformers here: kzread.info/dash/bejne/faScz7GDnq-nlKw.html

🎉🎉🎉thank you😊

@statquest

8 күн бұрын

bam! :)

thank you sm fr bro

@statquest

14 сағат бұрын

Any time!

Thanks!

@statquest

13 сағат бұрын

TRIPLE BAM!!! Thank you for supporting StatQuest!

Thanks a lot for for this free wonderful content. ❤😊

@statquest

Күн бұрын

Thank you!

Legend.

@statquest

Күн бұрын

:)

🎉🎉🎉

@statquest

Күн бұрын

Triple 🎉!

Triple Bam!!!

@statquest

Күн бұрын

:)

amazinggg

@statquest

14 сағат бұрын

Thanks!

BAM!!

@statquest

Күн бұрын

Thanks Nosson!

Bam!

@statquest

Күн бұрын

:)

Baaaam!❤

@statquest

Күн бұрын

:)

Ya misspelled ChatGPT - Generative Pre-trained Transformer

@statquest

Күн бұрын

Corrected! :)

GTP :)

@statquest

Күн бұрын

Corrected! ;)

I'm confused as to why the values would come from the ENCODER when computing the cross attention between the Encoder and Decoder. Shouldn't the values come from the decoder itself? So if I trained a model to translate from English to German, then wanted to switch out the German for Spanish, I'd expect the new decoder to know what to do with the output of the Encoder. But if the values are coming from the Encoder, then this wouldn't work.

@statquest

13 сағат бұрын

The idea is that the query in the decoder is used to determine how a potential word in the output is related to the words in the input. This done by using a query from the decoder and keys for all of the input words in the encoder. Then, once we have established how much (what percentages) a potential word in the output is related to all of the input word, we then have to determine what that percentage is of. It is of the values. And thus, the values have to come from the encoder. For more details, see: kzread.info/dash/bejne/rKyF27aEaNTbqbw.html

Sir can you include how to make the chatbot to hold a conversation with

@statquest

Күн бұрын

I'll keep that in mind.

🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻 Please please please show us how to train QVK Weights in detail 🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻 You showed us just a simple call to function. But we are curious how it did the math, what to train, and how it can changes values of the weights. ABC

@statquest

14 сағат бұрын

Every single weight and bias in a neural network is trained with backpropagation. To learn more about how this process works, see: kzread.info/dash/bejne/e4Jmus97mKyypJc.html kzread.info/dash/bejne/m62ilNydca_PmZs.html and kzread.info/dash/bejne/eX-O0bGBiKrJfNI.html

@yosimadsu2189

11 сағат бұрын

@@statquest Since both QVK Weights are splitted and the calculations are passing non neural network, imho the back propagation process is quite tricky. In the other hand, the fit function did not tell the order of calculations on each nodes.

GTP

@statquest

Күн бұрын

Corrected! :)

Wish you could be Prime Minister of the United Kingdom!

@statquest

Күн бұрын

Ha! :)

From scratch in pytorch, huh.

@statquest

Күн бұрын

I decided to skip doing it in assembly. ;)